library("here")
library("sjPlot")
library("dplyr")
library("lme4")
library("viridis")
library("lmerTest")
library("ggplot2")
library("gridExtra")
library("gt")
source("analysis_functions.R")
1. LFMM
1.1 Individual sampling
1.1.1 Summary plots
lfmm_ind <- format_lfmm(here(dirname(getwd()), "p3_methods", "outputs", "lfmm_indsampling_results.csv"))
summary_hplot(lfmm_ind, "K.1", colpal = "turbo")

summary_hplot(lfmm_ind, "TPRCOMBO", colpal = "plasma")

summary_hplot(lfmm_ind, "FDRCOMBO", colpal = "viridis", direction = -1)

1.1.2 Model summaries
run_lmer(lfmm_ind, "TPRCOMBO", table_main = "True Positive Rate")
| Predictors |
Sum Sq |
Mean Sq |
NumDF |
DenDF |
F value |
Pr(>F) |
| nsamp |
3.35 |
1.12 |
3.00 |
30706 |
282.80 |
4.3 × 10−181 |
| sampstrat |
0.46 |
0.15 |
3.00 |
30706 |
38.92 |
4.3 × 10−25 |
| K |
2.54 |
2.54 |
1.00 |
30706 |
642.55 |
2.6 × 10−140 |
| m |
0.62 |
0.62 |
1.00 |
30706 |
155.78 |
1.2 × 10−35 |
| phi |
27.10 |
27.10 |
1.00 |
30706 |
6.86K |
0.0 |
| H |
34.89 |
34.89 |
1.00 |
30706 |
8.83K |
0.0 |
| r |
0.82 |
0.82 |
1.00 |
30706 |
206.35 |
1.2 × 10−46 |
run_lmer(lfmm_ind, "FDRCOMBO", table_main = "False Discovery Rate")
| Predictors |
Sum Sq |
Mean Sq |
NumDF |
DenDF |
F value |
Pr(>F) |
| nsamp |
1.57K |
522.48 |
3.00 |
30706 |
3.05K |
0.0 |
| sampstrat |
33.55 |
11.18 |
3.00 |
30706 |
65.26 |
4.7 × 10−42 |
| K |
15.90 |
15.90 |
1.00 |
30706 |
92.82 |
6.2 × 10−22 |
| m |
29.08 |
29.08 |
1.00 |
30706 |
169.68 |
1.1 × 10−38 |
| phi |
5.20 |
5.20 |
1.00 |
30706 |
30.38 |
3.6 × 10−8 |
| H |
30.95 |
30.95 |
1.00 |
30706 |
180.63 |
4.6 × 10−41 |
| r |
0.09 |
0.09 |
1.00 |
30706 |
0.51 |
0.48 |
1.1.3 Megaplots
MEGAPLOT(lfmm_ind, "K.1", colpal = "turbo")

MEGAPLOT(lfmm_ind, "TPRCOMBO", colpal = "plasma")

MEGAPLOT(lfmm_ind, "FDRCOMBO", colpal = "viridis", direction = -1)

1.2 Site sampling
1.2.1 Summary plots
lfmm_site <- format_lfmm(here(dirname(getwd()), "p3_methods", "outputs", "lfmm_sitesampling_results.csv"))
summary_hplot(lfmm_site, "K.1", colpal = "turbo")

summary_hplot(lfmm_site, "TPRCOMBO", colpal = "plasma")

summary_hplot(lfmm_site, "FDRCOMBO", colpal = "viridis", direction = -1)

1.2.2 Model summaries
run_lmer(lfmm_site, "TPRCOMBO", table_main = "True Positive Rate")
| Predictors |
Sum Sq |
Mean Sq |
NumDF |
DenDF |
F value |
Pr(>F) |
| nsamp |
0.17 |
0.08 |
2.00 |
17268 |
29.98 |
1.0 × 10−13 |
| sampstrat |
0.19 |
0.10 |
2.00 |
17268 |
34.63 |
9.8 × 10−16 |
| K |
0.36 |
0.36 |
1.00 |
17268 |
131.53 |
2.4 × 10−30 |
| m |
0.61 |
0.61 |
1.00 |
17268 |
221.27 |
9.7 × 10−50 |
| phi |
2.25 |
2.25 |
1.00 |
17268 |
818.45 |
6.5 × 10−176 |
| H |
6.00 |
6.00 |
1.00 |
17268 |
2.18K |
0.0 |
| r |
0.27 |
0.27 |
1.00 |
17268 |
98.22 |
4.3 × 10−23 |
run_lmer(lfmm_site, "FDRCOMBO", table_main = "False Discovery Rate")
| Predictors |
Sum Sq |
Mean Sq |
NumDF |
DenDF |
F value |
Pr(>F) |
| nsamp |
22.32 |
11.16 |
2.00 |
17268 |
528.44 |
1.8 × 10−223 |
| sampstrat |
0.43 |
0.22 |
2.00 |
17268 |
10.21 |
3.7 × 10−5 |
| K |
0.23 |
0.23 |
1.00 |
17268 |
10.78 |
1.0 × 10−3 |
| m |
1.98 |
1.98 |
1.00 |
17268 |
93.64 |
4.3 × 10−22 |
| phi |
0.50 |
0.50 |
1.00 |
17268 |
23.79 |
1.1 × 10−6 |
| H |
0.36 |
0.36 |
1.00 |
17268 |
16.97 |
3.8 × 10−5 |
| r |
0.11 |
0.11 |
1.00 |
17268 |
5.36 |
0.021 |
1.2.3 Megaplots
MEGAPLOT(lfmm_site, "K.1", colpal = "turbo")

MEGAPLOT(lfmm_site, "TPRCOMBO", colpal = "plasma")

MEGAPLOT(lfmm_site, "FDRCOMBO", colpal = "viridis", direction = -1)

2. RDA
2.1 Individual sampling
2.1.1 Summary plots
rda_ind <- format_rda(here(dirname(getwd()), "p3_methods", "outputs", "rda_indsampling_results.csv"))
summary_hplot(rda_ind, "TPRCOMBO", colpal = "plasma")

summary_hplot(rda_ind, "FDRCOMBO", colpal = "viridis", direction = -1)

2.1.2 Model summaries
run_lmer(rda_ind, "TPRCOMBO", table_main = "True Positive Rate")
| Predictors |
Sum Sq |
Mean Sq |
NumDF |
DenDF |
F value |
Pr(>F) |
| nsamp |
0.70 |
0.23 |
3.00 |
30706 |
266.52 |
8.9 × 10−171 |
| sampstrat |
0.11 |
0.04 |
3.00 |
30706 |
41.03 |
1.9 × 10−26 |
| K |
0.31 |
0.31 |
1.00 |
30706 |
354.08 |
1.5 × 10−78 |
| m |
0.80 |
0.80 |
1.00 |
30706 |
925.77 |
2.3 × 10−200 |
| phi |
0.80 |
0.80 |
1.00 |
30706 |
919.89 |
4.0 × 10−199 |
| H |
0.76 |
0.76 |
1.00 |
30706 |
879.27 |
1.5 × 10−190 |
| r |
0.02 |
0.02 |
1.00 |
30706 |
21.56 |
3.4 × 10−6 |
run_lmer(rda_ind, "FDRCOMBO", table_main = "False Discovery Rate")
| Predictors |
Sum Sq |
Mean Sq |
NumDF |
DenDF |
F value |
Pr(>F) |
| nsamp |
0.04 |
0.01 |
3.00 |
30706 |
8.92 |
6.7 × 10−6 |
| sampstrat |
0.00 |
0.00 |
3.00 |
30706 |
0.28 |
0.84 |
| K |
0.02 |
0.02 |
1.00 |
30706 |
11.89 |
5.6 × 10−4 |
| m |
0.06 |
0.06 |
1.00 |
30706 |
39.03 |
4.2 × 10−10 |
| phi |
0.01 |
0.01 |
1.00 |
30706 |
9.29 |
2.3 × 10−3 |
| H |
0.05 |
0.05 |
1.00 |
30706 |
33.04 |
9.1 × 10−9 |
| r |
0.00 |
0.00 |
1.00 |
30706 |
2.40 |
0.12 |
1.1.3 Megaplots
MEGAPLOT(rda_ind, "TPRCOMBO", colpal = "plasma")

MEGAPLOT(rda_ind, "FDRCOMBO", colpal = "viridis", direction = -1)

2.2 Site sampling
2.2.1 Summary plots
rda_site <- format_rda(here(dirname(getwd()), "p3_methods", "outputs", "rda_sitesampling_results.csv"))
summary_hplot(rda_site, "TPRCOMBO", colpal = "plasma")

summary_hplot(rda_site, "FDRCOMBO", colpal = "viridis", direction = -1)

2.2.2 Model summaries
run_lmer(rda_site, "TPRCOMBO", table_main = "True Positive Rate")
| Predictors |
Sum Sq |
Mean Sq |
NumDF |
DenDF |
F value |
Pr(>F) |
| nsamp |
0.13 |
0.07 |
2.00 |
17268 |
141.35 |
1.3 × 10−61 |
| sampstrat |
0.02 |
0.01 |
2.00 |
17268 |
22.96 |
1.1 × 10−10 |
| K |
0.07 |
0.07 |
1.00 |
17268 |
156.63 |
8.8 × 10−36 |
| m |
0.13 |
0.13 |
1.00 |
17268 |
282.87 |
5.7 × 10−63 |
| phi |
0.13 |
0.13 |
1.00 |
17268 |
282.87 |
5.7 × 10−63 |
| H |
0.12 |
0.12 |
1.00 |
17268 |
265.42 |
3.1 × 10−59 |
| r |
0.00 |
0.00 |
1.00 |
17268 |
7.18 |
7.4 × 10−3 |
run_lmer(rda_site, "FDRCOMBO", table_main = "False Discovery Rate")
## boundary (singular) fit: see help('isSingular')
| Predictors |
Sum Sq |
Mean Sq |
NumDF |
DenDF |
F value |
Pr(>F) |
| nsamp |
0.00 |
0.00 |
2.00 |
17270 |
2.00 |
0.140 |
| sampstrat |
0.00 |
0.00 |
2.00 |
17270 |
0.00 |
1.000 |
| K |
0.00 |
0.00 |
1.00 |
17270 |
0.67 |
0.410 |
| m |
0.00 |
0.00 |
1.00 |
17270 |
6.01 |
0.014 |
| phi |
0.00 |
0.00 |
1.00 |
17270 |
6.01 |
0.014 |
| H |
0.00 |
0.00 |
1.00 |
17270 |
6.01 |
0.014 |
| r |
0.00 |
0.00 |
1.00 |
17270 |
0.67 |
0.410 |
2.2.3 Megaplots
MEGAPLOT(rda_site, "TPRCOMBO", colpal = "plasma")

MEGAPLOT(rda_site, "FDRCOMBO", colpal = "viridis", direction = -1)
